cooperation scaffolding might hinder students’ cooperation inlearning. The impacts of scaffolding on students' learning dispositions measured by MSLQ 23 wereexamined by comparing results between the post-test and the pre-test in terms of size effect, asshown in Table 10. According to the comparison, Group B enjoyed the increase in self-efficacy, intrinsic value, cognitive strategy use and self-regulation, but suffered intensified testanxiety. Group C, similar to Group D, experienced increase in self-efficacy and reduced testanxiety, but failed to develop in intrinsic value cognitive strategy use and self-regulation.However, Group D enjoyed the boldest increase in self-efficacy and largest decrease in testanxiety, but they suffered the largest
in a variety of STEM fields and were fromeither 4-year or 2-year institutions. Among the eight REU students, five were females and threewere males.REU Research ProjectsThroughout the 10-week summer program, REU students conducted four research projects,including 1) developing a self-regulation survey instrument for problem solving in engineering;2) studying students’ meta-cognitive strategies when learning engineering with computersimulation and animation; 3) studying students’ self-efficacy, perception of engineering, andengineering interest in the context of Mathematics Engineering Science Achievement (MESA)22 ; and 4) developing an instrument for exploring engineering design knowing and thinking.These four projects are briefly described
trainingorganization.Results22 undergraduate engineering students participating in the 2014 semester-long class participatedin pre- and post-class surveys. As mentioned above, self-efficacy has been shown to be anexcellent tool for measuring students for our key objectives. Figure 5 shows the results of the2014 semester-long class in comparison to the 2011, 2012, and 2013 fieldtrip classes and thecontrol group. Table 4 summarizes the improvements in the student survey’s following theclasses. Table 5 shows the standard deviation for each question and year. No, Not at All Yes, Definitely 3.4
course offered in Fall 2014 collaborating on designing, building, andtesting autonomous waste sorters. Teams from one section of 38 mechanical, aerospace, electrical,and chemical engineering students are paired with those of the other section with 43 computerscience, informatics, software engineering, computer systems engineering, industrial engineering,and engineering management students. While the teams from each section focus on differentaspects of the design, inter-disciplinary collaboration and system integration is required for asuccessful final product.The impact of this experience on students’ knowledge and self-efficacy of the engineering designprocess, their technical communication skills, and teamwork has been measured. A
of pre-CI scores. Interestingly,looking at the concept inventory scores for the top and bottom 20% of students measured byparticipation as presented in Table 2, the top 20% students for each cohort showed greaterimprovement when compared with the bottom 20%. For the small cohort, the percentageimprovements in CI scores were 64.9% and 72.9% for the bottom and top 20%, respectively. Forthe large cohort, the percentage improvements in CI scores were 9.1% and 47.3% for the bottomand top 20%, respectively. Thus the small cohort displayed greater performance gains overallregardless of participation level, while the gains for the large cohort showed greater difference onthe basis of participation level.Results from the qualitative self-efficacy
between students who intent to major in STEM fields and their peers whoplan a major outside of STEM. A survey that intends to measure student interest in engineeringas a trait, should be able to distinguish students indicating future interest in STEM from thosewho do not. This finding indicates that a need to refine the FIDES 1.0 in order to measureinterest in engineering as a psychological construct in a way that more accurately reflects ourunderstanding of the intended population.FIDES 2.0: Revised Instrument DevelopmentRevised Item Construction Revisions were made to the FIDES instrument on the basis of results from the pilot study.First, two additional indicators were added (content knowledge and self-efficacy). Second, toaddress
estimated and quantified by using a students’ self-reported Likert scale based on the timelengths and frequencies of each dimension in which students perform. The students’ learning outcome variables will be divided into two main categories: (1)learning performance in terms of deeper understanding of domain knowledge measured by usinga concept inventory, concept map construction, and course quizzes and exams; and (2) learningdisposition in terms of SRL skills, perceived value of SRL assessment, self-efficacy, identity, Page 26.1471.7engagement measured by using different questionnaires developed
, there are 1,148 active S-STEM grants at over 580 institutions of higher education inthe United States2.At the authors’ institution, three separate NSF S-STEM proposals have been funded since 2011.In this paper, the authors provide specific information on the approaches they used to write andimplement successful NSF S-STEM proposals. The paper also provides details on the impactthese programs are having at this institution, including strategies that have been successful inengaging students, enhancing student learning, and increasing self-efficacy and retention.BackgroundEast Carolina University (ECU) is a constituent institution of the North Carolina state systemthat is composed of sixteen institutions, consisting of every public educational
own skills in transforming writteninformation into visual form, without giving them so much aid that the software becomes acrutch. Grounded in the learning theory of Vtogsky, 11 this approach resonates with a rich legacy Page 26.243.3of software scaffolding approaches 12,13 in which learners are initially aided by modifications toproblems that make them initially more doable; the modifications are then gradually removed aslearners gain more skills. ChemProV would, in addition, give students an opportunity for earlysuccess in the material/energy balance class, leading to enhanced learning according to self-efficacy theory. 14In 2008 and 2009
levels of interest in engineering, their success andcompletion rates have been low due to a number of factors including low levels of preparationfor college-level work, especially in math; lack of awareness of academic and career options;lack of financial, academic, social and cultural capital needed for success; and lack of self-efficacy (i.e., students do not believe that they can succeed in engineering). To address thesebarriers to student success, Cañada College developed and implemented a number of programs tokeep students engaged and motivated towards achieving their academic goals. Among suchprograms is the Creating Opportunities for Minorities in Engineering, Technology, and Science(COMETS) program. Funded by a four-year grant from NASA
behavior during their first co-op term experiencesignificant impact on learning outcomes 9. Early socialization experiences, including social andcontent aspects, positively affect students’ non-technical skills 9 10. Studying the effects of co-opeducation before graduation will help educators and administrators understand student’s learningexperiences, especially the non-technical skills that participants build outside of the classroom.Co-op participants show increased self-efficacy, which is beneficial in sustaining academicperformance and persistence to graduation 11. Additionally, co-ops students report greatercertainty about career choice (increased career identity) and are more likely to get job related totheir major at graduation. Students
).Table 6Comparison of Means for STEM Confidence by Gender and School Gender School M Participating 3.67 Girls Comparison 3.61 Participating 3.84 Boys Comparison 3.35Our last two attitude scales examined student STEM self-efficacy. Exploratory factor analysisindicated that our self-efficacy items measured two dimensions: math and science self-efficacy;and engineering and technology self-efficacy. Math and science efficacy were measured using a4-item scale (α = .77) with responses ranging from 1 (not at all) to 4 (almost all of
together during various mini projects in-class and duringthe “Independent Study” lab sessions. The mentor/tutor worked with faculty members andstudents to identify topics that were considered to be difficult and reviewed them during theselabs as well. Students were also given the opportunity to study for courses that were not part ofthe SUCCEEd program.Measures of Impact, Preliminary Results and DiscussionAs a part of the SUCCEEd program, we wished to assess both student achievement and otherfactors that may contribute to student success in the program. Achievement was measured viastudents’ grades, tests and quizzes results, and project results. The college self-efficacy (CSE),which refers to the students’ belief that they can succeed in college
tasks are generallygood predictors of subsequent performance on those tasks 27 and are positively correlated withdifferent identity-related constructs like attainment value and identification. 28 Consequently,self-efficacy or other perceptions of competence for performing engineering tasks seems apotentially important outcome for capstone design in terms of both performance and identitydevelopment.Discussion and ImplicationsAs the results above indicate, students in this study described outcomes from the capstone designexperience that align with various facets of their identity as engineers. Their sense of enteringinto a community as colleagues represents an interpersonal component, in which experiencedengineers recognize them as engineers. The
Metacognitive Self-regulation Intrinsic Goal Orientation Extrinsic Goal Orientation Task Value Control of Learning Self-efficacy Test Anxiety Time/Study Management Effort Regulation
.Simpson, et al. 9 believe that interdisciplinary experience is more representative of what studentswill find in the real world and advocate interdisciplinary capstone projects. Schaffer, et al. 10have concluded – based on their study of 256 students from 60 teams - that Cross disciplinaryTeam Learning (CDTL) increases self-efficacy across all respondents. Apelian11 believes thatone of the important skills for the 21stcentury engineer is the ability to work with anybodyanywhere. He concludes that we need to educate engineers such that they understand the societalcontext of their work and have an understanding of the human dimension around the globe,coupled with innovation and creativity. Michaelsen, et al.12 have claimed that innovation
Foundation,Division of Research and Learning in Formal and Informal Settings, 2010.37. Carberry A, Ohland M, Lee HS. Measuring engineering design self-efficacy. Journal ofEngineering Education. 2010;99(1):71-9. Page 26.670.8
attitude included several stereotypicalstatements that could indicate students’ level of understanding of basic job functions. Nofield of engineering was specified in the attitude survey. Then the study asked students toidentify 5 types of engineers and state one example of the work that type of engineer did.Less than 5% of the 300 plus students included in the survey were able to correctlyidentify 5 types of engineers. Close to half of the students had no opinion of engineers’involvement in business decisions or how much time engineers spent in the lab.16There are many studies that explore differences in perceptions by ethnicity or gender.These studies generally fall into either aspirational studies or self-efficacy studies. Inother words, why do
self-efficacy, sense of belonging, identification and identityintegration. Often, negative experiences are the result of subtle bias or schemas that all studentsbring with them into their teams, and occur despite the employment of best practices in teamformation.This paper presents a summary of a contemporary understanding of this phenomenon aspresented by several individual researchers covering the fields of stereotype threat, engineeringdesign, teamwork, motivation, and race, gender and their intersections. The content of this paperwas generated by collecting the individual responses of each researcher to a set of promptsincluding: • examples of how students can be marginalized in engineering teamwork and what governing
financial pressures). Hutchison, Follman, Sumpter, and Bodner6found that student retention was greatly impacted by students’ self-efficacy, which in turn wasimpacted by factors such as motivation, understanding of material, and social influences(including peers and faculty). Finally, Bernold, Spurlin, and Anson3 found that persistence inengineering is related to both student learning styles and study habits, as well as teachingmethodologies.Adding to the existing body of literature, ASEE’s publication on best practices in engineeringretention1 highlighted the wide range of programs that universities have developed in reaction tothe various issues that affect student persistence. Almost half of the universities profiled in thepublication had some
. Page 26.479.1 c American Society for Engineering Education, 2015 Designing Effective Project-based Learning Experience using Participatory Design ApproachAbstractThis paper presents the progress and findings of the second stage of an NSF sponsoredinterdisciplinary research project that aims at developing guidelines of effective instructionaldesign using collaborative PBL (CPBL) to boost the self-efficacy of minority students inengineering. To achieve the above goal, an exploratory case study was conducted, where we firstutilized an innovative instructional design strategy called Participatory Design Approach toimprove the curricular structure and CPBL model in a pilot course
studentengagement is commonly acknowledged to significantly benefit the students as well as thestudent mentors involved in the program. Data from an initial student survey that measures theefficacy of the proposed mentorship program is included in this paper and these data arediscussed in detail. A 1-5 Likert scale is used for quantitative analysis of the data in order toevaluate the self-efficacy of the program. The group size of the mentorship cohort has beenlimited to a maximum of thirty students at this stage. Preliminary analysis of the data indicatesthat the participating students have a strongly positive opinion of the program.Keywords: Mentorship, Engineering, Project-based Learning (PBL).1. IntroductionMentoring is commonly acknowledged as a means
, including e-mails, as well as basics of executivesummaries, memos, and other reports students may encounter in their careers.On the first day of class, students are given a survey on communication background and self-efficacy. The survey aims to understand student perspectives on communication, experiences,career goals, and course expectations. The self-efficacy component of the survey providesinformation regarding the individual student’s comfort with and attitude towards differentaspects of communication, and this is repeated at the end-of-semester in a final survey. Thisbefore-and-after administration of the survey provides a means for measuring student growthduring the course.Peer and instructor feedback and opportunities for revision are built
algebra and in improving students’ mathematics self-efficacy,” as measured by theMathematics Self-Efficacy Scale. Further, it was observed that “online homework may be evenmore effective for helping the large population of college algebra students who enroll in thecourse with inadequate prerequisite math skills.” Some universities report that students performbetter on exams when using WeBWorK thus boosting student performance11. In most cases, theimprovement was small, but nonetheless statistically significant compared to classes withoutWeBWorK6.One study found that student preferences for online homework over traditional homework Page
cohesion, team self-efficacy, and satisfaction, and reduce team conflict.Study 6 will explore the effect of structured team experiences and use of a peer evaluation system on team skills and team-member effectiveness. Prior research has found that completing peer evaluations familiarizes students with team skills9,10 and improves new teammates’ satisfaction with those team members on a future team.1Study 7 will explore the effect of five feedback alternatives on team performance, Page 26.1566.4 satisfaction, team cohesion, team efficacy and team conflict: (1) self and peer evaluation data collected but no feedback given, (2) feedback
accurately perceive one’s own skill level.2 Prior research shows that this greater self- understanding is evidence of learning; in other words, these metacognitive gains are evidence of concomitant cognitive gains.7,8Study 4 will determine whether giving students feedback on the degree to which their ratings match those of other raters improves their rating practices.Study 5 will explore the effect of cognitive model development (measured by a knowledge test as in Study 2) on team performance and team-member effectiveness. Training members of teams to develop a more accurate cognitive model of teamwork should increase team performance, team cohesion, team self-efficacy, and satisfaction, and reduce team conflict.Study 6 will explore
influencing their self-efficacy, the development of their career interest goalsand their academic course outcomes as related to studying science, technology, engineering andmathematics (STEM). This study is unique in that it was also designed to identify experiencesthat appear to contribute to women’s identity development and self-confidence and includes asubstantial representation of Latina women’s voices. Data was collected and analyzed to identifyif similar patterns exist between subjects and if so, which are the greater influencers in theirdecision to select a STEM major and to persist beyond the critical first two years ofundergraduate studies.The literature of socialization and identity development as related to women as STEM learners indiverse
)changes over time. There have also been several reviews of the literature on mentoring specificto higher education42-45. Reviews by Jacobi43, Roberts45, and Crisp and Cruz44 have yieldedsimilar characterizations to those offered by D’Abate et al. and Eby et al., though all agree that itis difficult to reach a unified definition or a quantitatively validated framework, even within asingle domain such as higher education. Mentoring is, however, consistently linked to academicsuccess (e.g. increased GPA), as well as increases in self-efficacy, integration into thecommunity, retention, career goals, intention to persist and much more. While such broaddefinitions and outcomes provide important starting points for understanding mentoring inengineering
. Dissemination Partners include the Journal of Engineering Entrepreneurship [JEEN], The NSF sponsored Epicenter Project - The National Center for Engineering Pathways to Innovation at Stanford University and Venture Well, and ASEE‘s Entrepreneurship and Innovation Division.Instrument Development Process (Penn State team leads) Instrument research. In 2013/2014, 39 validated instruments that measure constructs related to one or more of our 20 characteristics of engineering innovativeness were identified from the Entrepreneurship, Information Processing, and Motivation/Self Efficacy literature. The constructs underlying these instruments were critically reviewed in terms of the elements of cognitive function they